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文章摘要
一种基于改进负荷矩的台区电压快速估算方法
A fast voltage estimation method based on improved load moment
Received:September 18, 2018  Revised:September 18, 2018
DOI:10.19753/j.issn1001-1390.2020.02.007
中文关键词: 负荷矩  归一化系数  BP神经网络  Levenberg-Marquardt算法
英文关键词: load moment  normalization coefficient  BP neural network  Levenberg-Marquardt algorithm
基金项目:国家电网公司科技项目(适应新型城镇化的配电网协调规划关键技术及实证研究,52120916000400k000000)
Author NameAffiliationE-mail
HU Bin* State Grid Anhui Economic Research Institute binhu1990@foxmail.com 
WANG Xuli State Grid Anhui Economic Research Institute wangxl@ah.sgcc.com 
YE Bin State Grid Anhui Economic Research Institute yeb@ah.sgcc.com 
MA Jing State Grid Anhui Economic Research Institute maj@ah.sgcc.com 
YE Bin State Grid Anhui Economic Research Institute yebin@ah.sgcc.com 
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中文摘要:
      针对不同截面导线混接给负荷矩计算带来的困难,提出了一种负荷矩归一化方法,在保证线路压降相同的情况下,能够通过归一化系数统一线路型号,将复杂的配电网络简单化、标准化。在此基础上,建立了节点负荷矩与节点电压之间的映射关系,通过基于Levenberg-Marquardt算法的BP神经网络,实现了对台区节点电压的全覆盖估算,克服了传统梯度下降算法在收敛速度、计算稳定性上的缺陷,所需训练样本少,计算效率高。选取某实际台区网络进行了仿真分析,算例结果验证了本文方法的有效性。
英文摘要:
      In order to solve the difficulty of load moment calculation of different cross section wires, a method of load moment normalization is proposed. In the case of ensuring the same voltage drop of the conductor, the model of wire can be unified through the normalization coefficient, and the complex distribution network is simplified and standardized. On this basis, the mapping relationship between the node load moment and the node voltage is established. Through the BP neural network based on the Levenberg-Marquardt algorithm, the full coverage estimation of the node voltage is realized, and the shortcomings of the traditional gradient descent algorithm in the convergence speed and the calculation stability are overcome. The required training samples are few, and the calculation efficiency is high. A practical network is selected for simulation analysis. The effectiveness of the proposed method is verified.
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